• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.6
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• pp.1010-1019
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• 1994

It is shown that there exists a nonlinear mapping which transforms image features and their changes to the desired camera motion without measuring of the relative distance between the camera and the object. This nonlinear mapping can eliminate several difficulties occurring in computing the inverse of the feature Jacobian as in the usual feature-based visual feedback control methods. Instead of analytically deriving the closed form of this mapping, a Fuzzy Membership Function-based Neural Network (FMFNN) incorporating a Fuzzy-Neural Interpolating Network is used to approximate the nonlinear mapping. Several FMFNN's are trained to be capable of tracking a moving object in the whole workspace along the line of sight. For an effective implementation of the proposed FMF network, an image feature selection process is investigated. Finally, several numerical examples are presented to show the validity of the proposed visual servoing method.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.1
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• pp.94-98
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• 2015

Recently, with the rapid advancement in information and computer vision technology, a CCTV system using object recognition and tracking has been studied in a variety of fields. However, it is difficult to recognize a precise object outdoors due to varying pixel values by moving background elements such as shadows, lighting change, and moving elements of the scene. In order to adapt the background outdoors, this paper presents to analyze a variety of background models and proposed background update algorithms based on the weight factor. The experimental results show that the accuracy of object detection is maintained, and the number of misrecognized objects are reduced compared to previous study by using the proposed algorithm.

• Journal of Internet Computing and Services
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• v.5 no.4
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• pp.77-94
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• 2004

Recently, the needs of index structure which manages moving objects efficiently have been increased because of the rapid development of location-based techniques. Existing index structures frequently need updates because moving objects change continuatively their positions. That caused entire performance loss of the index structures. In this paper, we propose a new index structure called the TPKDB-tree that is a spatio-temporal index structure based on KDB-tree. Our technique optimizes update costs and reduces a search time for moving objects and reduces unnecessary updates by expressing moving objects as linear functions. Thus, the TPKDB-tree efficiently supports the searches of future positions of moving objects by considering the changes of moving objects included in the node as time-parameter. To maximize space utilization, we propose the new update and split methods. Finally, we perform various experiments to show that our approach outperforms others.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.2
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• pp.402-409
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• 2007

In this paper recognized for trajectory using Condensation algorithm. In this pater used fuzzy controller for recognized trajectory using fuzzy reasoning. The fuzzy system tract to the three-dimensional space for raw and roll movement. The joint angle ${\theta}_1$ of the manipulator rotate from $0^{\circ}\;to\;360^{\circ}$, and the joint angle ${\theta}_2$ rotate from $0^{\circ}\;to\;180^{\circ}$. The moving object of velocity display for recognition without error using Condensation algorithm. The tracking system demonstrated the reliability of proposed algorithm through simulation against used trajectory.

• Journal of Convergence for Information Technology
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• v.9 no.3
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• pp.30-35
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• 2019

An unattended recording system based on smartphone based image image tracking is rapidly developing. Among the existing products, a system that automatically tracks and rotates the object to be photographed using an infrared signal is very expensive for general users. Therefore, this paper proposes a mobile unattended recording system that enables automatic recording by anyone who uses a smartphone. The system consists of a commercial mobile camera, a servomotor that moves the camera from side to side, a microcontroller to control the motor, and a commercial wireless Bluetooth Earset for video audio input. In this paper, we designed a system that enables unattended recording through image tracking using smartphone.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.838-846
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• 2004

In the case where both a camera and a target are moving at the same time, the image background is successively changed, and the overlap with other moving objects is apt to be generated. The snake algorithms have been variously used in tracking the object, but it is difficult to be applied in the excessive overlap with other objects and the large bias between the snake and the target. To solve this problem, this paper presents an extended snake model. It includes an additional energy function which considers the temporal variation rate of the snake's area and a SSD algorithm which generates the template adaptive to the snake detected in the previous frame. The new energy function prevents the snake from over-shrinking or stretching and the SSD algorithm with adaptively changing template allows the prediction of the target's position in the next frame. The experimental results have shown that the proposed algorithm successfully tracks the target even when the target is temporarily occluded by other objects.

• The Journal of the Korea Contents Association
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• v.7 no.6
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• pp.9-21
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• 2007

In this paper, the hybrid methods are suggested, which use the direction angle information to present running trajectory and track the past locations through a small amount of vehicle's location information. In order to prove the effectiveness of the new technique suggested here, vehicle's location information are collected by running the vehicles moving objects under various conditions. Using the location informations and direction angle information collected with time intervals, the vehicl e's location information is abstracted, compared and analyzed. and I have proved that the suggested techniques are more effective by comparing them with others in various methods such as GPS TrackMaker, difference image techniques, consistency comparison, quantity comparison, vehicle's running distances and so on.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.79-84
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• 2005

In this paper, we developed an omni-directional surveillance and motion detection method. The fish-eye lens provides a wide field of view image. Using this image, the equi-distance model for the fish-eye lens is applied to get the perspective and panorama images. Generally, we must consider the trade-off between resolution and field of view of an image from a camera. To enhance the resolution of the result images, some kind of interpolation methods are applied. Also the moving edge method is used to detect moving objects for the object tracking.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.885-888
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• 2018

This paper researches a way of detecting fish robots moving in an aquarium. The fish robot was designed and developed for interactions with humans in aquariums. It was studied merely to detect a moving object in an aquarium because we need to find the positions of moving fish robots. The intention is to recognize the location of robotic fish using an image processing technique and a video camera. This method is used to obtain the velocity for each pixel in an image, and assumes a constant velocity in each video frame to obtain positions of fish robots by comparing sequential video frames. By using this positional data, we compute the distance between fish robots using a mathematical expression, and determine which fish robot is leading and which one is lagging. Then, the lead robot will wait for the lagging robot until it reaches the lead robot. The process runs continuously. This system is exhibited in the Busan Science Museum, satisfying a performance test of this algorithm.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1179-1186
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• 2013

In this paper, an efficient vehicle detection and tracking algorithm for detection incident in tunnel is proposed. The proposed algorithm consists of three steps. The first one is a step for background estimates, low computational complexity and memory consumption Running Gaussian Average (RGA) is used. The second step is vehicle detection step, Adaboost algorithm is applied to this step. In order to reduce false detection from a relatively remote location of the vehicles, local features according to height of vehicles are used to detect vehicles. If the local features of an object are more than the threshold value, the object is classified as a vehicle. The last step is a vehicle tracking step, the Kalman filter is applied to track moving objects. Through computer simulations, the proposed algorithm was found that useful to detect and track vehicles in the tunnel.